教育中人工智能焦虑的系统回顾

Xiaolan Wu, Hui Li
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引用次数: 0

摘要

本系统研究考察了教育环境中人工智能焦虑的发生,利用了从WOS和SCOPUS数据库中获得的32篇同行评审文章的见解。本研究将现有知识整合为五大主题类别:(1)AI焦虑的流行、概念化和利益相关者差异;(2)人工智能焦虑及其与自我效能感、行为意向的关系;(3)人工智能焦虑对学习行为和学习结果的影响;(4)人口统计学和情境因素在人工智能焦虑中起调节作用;(5)人工智能焦虑缓解策略,提出缓解人工智能相关担忧的干预框架。这一分析强调了人工智能焦虑的复杂性,它对教育实践的影响,以及需要采取具体措施来促进对学习环境中人工智能整合的有利态度。本研究确定了基本差距和未来的研究课题,有助于在人工智能时代创造更具包容性和适应性的教育环境。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A systematic review of AI anxiety in education

This systematic study examines the occurrence of AI anxiety in educational settings, utilizing insights from 32 peer-reviewed articles obtained from the WOS and SCOPUS databases. The research consolidates existing knowledge into five topic categories: (1) Prevalence, conceptualization, and stakeholder differences of AI Anxiety; (2) AI Anxiety and its relationship with self-efficacy and behavioral intentions; (3) Impact of AI anxiety on learning behaviors and outcomes; (4) Demographic and contextual factors as moderators in AI anxiety; and (5) Mitigation strategies for AI anxiety, proposing intervention frameworks to alleviate AI-related concerns. This analysis highlights the complex nature of AI anxiety, its effects on educational practices, and the need for specific initiatives to promote favorable attitudes towards AI integration in learning settings. This study identifies essential gaps and future research topics, contributing to the creation of more inclusive and adaptive educational environments in the age of artificial intelligence.

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